A Novel Fuzzy Approach for State Estimation of Nonlinear Hybrid Systems Using Particle Filtering Method

2011 ◽  
Vol 14 (4) ◽  
pp. 974-990 ◽  
Author(s):  
Karim Salahshoor ◽  
M. Foad Samadi
Keyword(s):  
State Estimation ◽  
Hybrid Systems ◽  
Particle Filtering ◽  
Fuzzy Approach ◽  
Filtering Method ◽  
Nonlinear Hybrid

Comparison of state estimation techniques for nonlinear hybrid systems

SIMULATION ◽  
2016 ◽  
Vol 92 (4) ◽  
pp. 357-376
Author(s):  
Gan Zhou ◽  
Gautam Biswas ◽  
Wenfeng Zhang ◽  
Qi Zhao ◽  
Wenquan Feng
Keyword(s):  
State Estimation ◽  
Hybrid Systems ◽  
Estimation Techniques ◽  
Nonlinear Hybrid

scholarly journals Mode discernibility and bounded-error state estimation for nonlinear hybrid systems

Automatica ◽  
2018 ◽  
Vol 91 ◽  
pp. 118-125
Author(s):  
Nacim Ramdani ◽  
Louise Travé-Massuyès ◽  
Carine Jauberthie
Keyword(s):  
State Estimation ◽  
Hybrid Systems ◽  
Bounded Error ◽  
Error State ◽  
Nonlinear Hybrid

Reachability analysis of nonlinear hybrid systems based on polyhedron inclusion

2013 ◽  
Vol 33 (5) ◽  
pp. 1289-1293
Author(s):  
Jin ZOU ◽  
Wang LIN ◽  
Yong LUO ◽  
Zhenbing ZENG
Keyword(s):  
Hybrid Systems ◽  
Reachability Analysis ◽  
Nonlinear Hybrid

scholarly journals Dynamic Indoor Localization Using Maximum Likelihood Particle Filtering

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1090
Author(s):  
Wenxu Wang ◽  
Damián Marelli ◽  
Minyue Fu
Keyword(s):  
Maximum Likelihood ◽  
Particle Filtering ◽  
Indoor Localization ◽  
Real Data ◽  
High Accuracy ◽  
Classical Particle ◽  
Popular Approach ◽  
Filtering Method ◽  
Essential Idea ◽  
Number Of Particles

A popular approach for solving the indoor dynamic localization problem based on WiFi measurements consists of using particle filtering. However, a drawback of this approach is that a very large number of particles are needed to achieve accurate results in real environments. The reason for this drawback is that, in this particular application, classical particle filtering wastes many unnecessary particles. To remedy this, we propose a novel particle filtering method which we call maximum likelihood particle filter (MLPF). The essential idea consists of combining the particle prediction and update steps into a single one in which all particles are efficiently used. This drastically reduces the number of particles, leading to numerically feasible algorithms with high accuracy. We provide experimental results, using real data, confirming our claim.

scholarly journals CGMurphi: Automatic synthesis of numerical controllers for nonlinear hybrid systems

2013 ◽  
Vol 19 (1) ◽  
pp. 14-36 ◽  
Author(s):  
Giuseppe Della Penna ◽  
Benedetto Intrigila ◽  
Daniele Magazzeni ◽  
Igor Melatti ◽  
Enrico Tronci
Keyword(s):  
Hybrid Systems ◽  
Automatic Synthesis ◽  
Nonlinear Hybrid

Set-membership filtering for automatic guided vehicles with unknown-but-bounded noises

2021 ◽  
pp. 014233122110436
Author(s):  
Hao Yang ◽  
Yilian Zhang ◽  
Wei Gu ◽  
Fuwen Yang ◽  
Zhiquan Liu
Keyword(s):  
State Estimation ◽  
Estimation Algorithm ◽  
The State ◽  
Estimation Problem ◽  
Filtering Method ◽  
Automatic Guided Vehicles ◽  
Tracking Process ◽  
Set Membership ◽  
Text Filtering ◽  
System States

This paper is concerned with the state estimation problem for an automatic guided vehicle (AGV). A novel set-membership filtering (SMF) scheme is presented to solve the state estimation problem in the trajectory tracking process of the AGV under the unknown-but-bounded (UBB) process and measurement noises. Different from some existing traditional filtering methods, such as Kalman filtering method and [Formula: see text] filtering method, the proposed SMF scheme is developed to provide state estimation sets rather than state estimation points for the system states to effectively deal with UBB noises and reduce the requirement of the sensor precision. Then, in order to obtain the state estimation ellipsoids containing the true states, a set-membership estimation algorithm is designed based on the AGV physical model and S-procedure technique. Finally, comparison examples are presented to illustrate the effectiveness of the proposed SMF scheme for an AGV state estimation problem in the present of the UBB noises.

Safety Verification of Nonlinear Hybrid Systems Based on Bilinear Programming

2018 ◽  
Vol 37 (11) ◽  
pp. 2768-2778 ◽  
Author(s):  
Yifan Zhang ◽  
Zhengfeng Yang ◽  
Wang Lin ◽  
Huibiao Zhu ◽  
Xin Chen ◽  
...  
Keyword(s):  
Hybrid Systems ◽  
Bilinear Programming ◽  
Safety Verification ◽  
Nonlinear Hybrid

Applications of numerical optimal control to nonlinear hybrid systems

2007 ◽  
Vol 1 (2) ◽  
pp. 264-279 ◽  
Author(s):  
Shangming Wei ◽  
Kasemsak Uthaichana ◽  
Miloš Žefran ◽  
Raymond A. DeCarlo ◽  
Sorin Bengea
Keyword(s):  
Optimal Control ◽  
Hybrid Systems ◽  
Nonlinear Hybrid
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